Psychoradiology最新文献

Background: We previously reported lower baseline arteriolar cerebral blood volumes (CBVa) in almost all gray matter regions in a cohort of individuals with schizophrenia of varying ages and disease duration. The extent to which decreased CBVa is also present in recent-onset schizophrenia, and how this impacts neurovascular coupling, remains to be determined. In this study, we sought to determine the extent of CBVa deficits in recent-onset schizophrenia and the relationship of CBVa to region-specific resting-state neural activity.

Methods: Using 7 T MRI, CBVa was measured in 90 regions using 3D inflow-based vascular-space-occupancy (iVASO) imaging in 16 individuals with recent-onset schizophrenia (disease duration: x̄ = 1.18 ± 1.4 years) and 12 age-matched controls. Resting-state functional MRI (rs-fMRI) was used to determine fractional amplitudes of low-frequency fluctuations (fALFF) and intrinsic connectivity (ICC) in spontaneous blood oxygen level-dependent (BOLD) signal. The region-specific relationship between CBVa and fALFF was determined as an index of neurovascular coupling.

Results: Compared with healthy participants, CBVa was lower in individuals with schizophrenia in almost all brain regions, with a global effect size of 0.23 and regional effect sizes up to 0.41. Individuals with schizophrenia also exhibited lower fALFF diffusely across cortical and subcortical gray matter regions. Ratios of mean regional CBVa to fALFF and ICC were significantly lower in patients in numerous brain regions.

Conclusion: These findings indicate that early-stage schizophrenia is characterized by widespread microvascular abnormalities and associated resting-state deficits in neural activity, suggesting that abnormalities in neurovascular coupling may contribute to the pathophysiology of schizophrenia.

Schizophrenia is a severe psychiatric disorder characterized by widespread white matter (WM) alterations, manifesting as neurodevelopmental deficits and dysconnectivity abnormalities. Over the past two decades, studies have focused on the clinical high-risk (CHR) stage of psychosis and have yielded fruitful information on WM abnormalities that exist prior to the full onset of psychosis, shedding light on biological mechanisms underlying psychosis development. This review presents a summary of current findings on cross-sectional and longitudinal WM alterations in individuals with CHR and their links to clinical symptoms and neurocognitive dysfunction. Next, we review the utilization of WM characterization in predicting clinical outcomes. Taken together, the literature suggests the clinical significance of WM characteristics and their great potential in predicting the conversion to psychosis, despite some methodological and conceptual challenges that remain to be addressed in future studies. Future CHR research would greatly benefit from utilizing WM to guide pharmacological and non-pharmacological targeted treatments, optimize clinical prediction models, and enable more accurate clinical care.

Background: The hippocampus has been widely reported to be involved in the neuropathology of major depressive disorder (MDD). All the previous researches adopted group-level hippocampus subregions atlas to investigate abnormal functional connectivities in MDD in absence of capturing individual variability. In addition, the molecular basis of functional impairments of hippocampal subregions in MDD remains elusive.

Objective: We aimed to reveal functional disruptions and recovery of individual hippocampal subregions in MDD patients before and after ECT and linked these functional connectivity differences to transcriptomic profiles to reveal molecular mechanism.

Methods: we used group guided individual functional parcellation approach to define individual subregions of hippocampus for each participant. Resting-state functional connectivity (FC) analysis of individual hippocampal subregions was conducted to investigate functional disruptions and recovery in MDD patients before and after ECT. Spatial association between functional connectivity differences and transcriptomic profiles was employed to reveal molecular mechanism.

Results: MDD patients showed increased FCs of the left tail part of hippocampus with dorsolateral prefrontal cortex and middle temporal gyrus while decreased FC with primary visual cortex. These abnormal FCs in MDD patients were normalized after ECT. In addition, we found that functional disruptions of the left tail part of hippocampus in MDD were mainly related to synaptic signaling and transmission, ion transport, cell-cell signaling and neurogenesis.

Conclusion: Our findings provide initial evidence for functional connectome disruption of individual hippocampal subregions and their molecular basis in MDD.

Brain network control theory (NCT) is a groundbreaking field in neuroscience that employs system engineering and cybernetics principles to elucidate and manipulate brain dynamics. This review examined the development and applications of NCT over the past decade. We highlighted how NCT has been effectively utilized to model brain dynamics, offering new insights into cognitive control, brain development, the pathophysiology of neurological and psychiatric disorders, and neuromodulation. Additionally, we summarized the practical implementation of NCT using the nctpy package. We also presented the doubts and challenges associated with NCT and efforts made to provide better empirical validations and biological underpinnings. Finally, we outlined future directions for NCT, covering its development and applications.

This review examines the methodological challenges and advancements in laminar functional magnetic resonance imaging (fMRI). With the advent of ultra-high-field MRI scanners, laminar fMRI has become pivotal in elucidating the intricate micro-architectures and functionalities of the human brain at a mesoscopic scale. Despite its profound potential, laminar fMRI faces significant challenges such as signal loss at high spatial resolution, limited specificity to laminar signatures, complex layer-specific analysis, the necessity for precise anatomical alignment, and prolonged acquisition times. This review discusses current methodologies, highlights typical challenges in laminar fMRI research, introduces innovative sequence and analysis methods, and outlines potential solutions for overcoming existing technical barriers. It aims to provide a technical overview of the field's current state, emphasizing both the impact of existing hurdles and the advancements that shape future prospects.

Background: The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.

Objective: This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.

Methods: Based on independent systematic reviews, we identified the neuromodulation targets of the rt-fMRI-NF (in acute and chronic pain) and funcSurg (in chronic pain) studies. We then characterized the underlying functional networks using a subsample of the 7 T resting-state fMRI dataset from the Human Connectome Project. Principal component analyses (PCA) were used to identify dominant patterns (accounting for a cumulative explained variance >80%) within the obtained functional maps, and the overlap between these PCA maps and canonical intrinsic brain networks (default, salience, and sensorimotor) was calculated using a null map approach.

Results: The anatomical targets used in rt-fMRI-NF and funcSurg approaches are largely distinct, with the middle cingulate cortex as a common target. Within the investigated canonical rs-fMRI networks, these approaches exhibit both divergent and overlapping functional connectivity patterns. Specifically, rt-fMRI-NF approaches primarily target the default mode network (P value range 0.001-0.002) and the salience network (P = 0.002), whereas funcSurg approaches predominantly target the salience network (P = 0.001) and the sensorimotor network (P value range 0.001-0.023).

Conclusion: Key hubs of the salience and sensorimotor networks may represent promising targets for the therapeutic application of rt-fMRI-NF in chronic pain.

The prefrontal cortex (PFC) is a critical non-invasive brain stimulation (NIBS) target for treating depression. However, the alterations of brain activations post-intervention remain inconsistent and the clinical moderators that could improve symptomatic effectiveness are unclear. The study aim was to systematically review the effectiveness of NIBS on depressive symptoms targeting PFC in functional magnetic resonance imaging (fMRI) studies. In our study, we delivered a combined activation likelihood estimation (ALE) meta-analysis and meta-regression. Until November 2020, three databases (PubMed, Web of Science, EMBASE) were searched and 14 studies with a total sample size of 584 were included in the ALE meta-analysis; after NIBS, four clusters in left cerebrum revealed significant activation while two clusters in right cerebrum revealed significant deactivation (P < 0.001, cluster size >150 mm³). Eleven studies were statistically reanalyzed for depressive symptoms pre-post active-NIBS and the pooled effect size was very large [(d = 1.82, 95%CI (1.23, 2.40)]; significant moderators causing substantial heterogeneity (Chi squared = 75.25, P < 0.01; I ² = 87%) were detected through subgroup analysis and univariate meta-regression. Multivariate meta-regression was then conducted accordingly and the model suggested good fitness (Q = 42.32, P < 0.01). In all, NIBS targeting PFC balanced three core depressive-related neurocognitive networks (the salience network, the default mode network, and the central executive network); the striatum played a central role and might serve as a candidate treatment biomarker; gender difference, treatment-resistant condition, comorbidity, treatment duration, and localization all contributed to moderating depressive symptoms during NIBS. More high-quality, multi-center randomized controlled trails delivering personalized NIBS are needed for clinical practice in the future.

From July 20 to 22, 2024, the ISMRM Endorsed Workshop on MR for Psychiatry was held in Chengdu City, China. This prestigious event attracted numerous academic elites worldwide, and Professor Benjamin Becker from the University of Hong Kong was invited. On the morning of July 20, during the "Advances in MR Technology" session, Professor Becker delivered an engaging lecture entitled "Novel approaches to precision MRI-imaging of human emotion." His presentation was met with great enthusiasm and sparked lively discussions among the participants. Following the conference, the Psychoradiology journal interviewed Professor Becker. In the interview, Benjamin emphasized the significant role of interdisciplinary collaboration, spanning various fields including psychology, neuroscience, clinical medicine, biomedical engineering, and computer science. Professor Becker firmly believed that such collaboration was crucial for a deeper understanding of the brain and psychiatric disorders. Additionally, he highly valued the importance of international cooperation, especially in addressing global mental health issues and challenges related to psychiatric disorders.